1. Field of the Invention
The invention relates to variation in spectrometer instruments. More particularly the invention relates to characterizing spectrometer instruments by classifying their spectral responses into a limited number of clusters and developing calibration transfer models between clusters that compensate for instrument variations.
2. Description of the Prior Art
Many of the analytical applications for spectrometers require calibration data sets that are time-consuming and expensive to create. Typically, these calibrations are highly specific. For example, apparently identical instruments produced by the same manufacturer may exhibit minor instrument variations; such variations may be seen when one instrument is built with a component that varies slightly from the same component in another instrument. In addition, a calibration set for an instrument produced by one manufacturer is generally not suitable for a similar instrument produced by another manufacturer. Furthermore, repairs to a single instrument can cause the instrument's spectral response to vary. As an instrument ages, it's spectral response may change. An instrument's spectral response may vary according to fluctuations in the operating environment. In applications requiring analysis of very low concentration analytes, non-invasive blood glucose prediction, for example, even minor instrument variation can introduce an unacceptable degree of error into the analysis. Providing another calibration model that takes the instrument's current spectral response into account can compensate for instrument variation. However, development of new calibration models is time-consuming, labor-intensive and costly.
In the development of spectroscopy-based analyzers for biomedical applications, there is a need for production of thousands to as many as millions of analyzers for a specific application. No methodology exists for providing calibrations for large numbers of instruments quickly and inexpensively.
Therefore, efforts have been directed at transferring calibrations from one analyzer to another. See, for example, E. Bouveresse, C. Hartmann,. D. Massart, I. Last, K. Prebble, Standardization of near-infrared spectrometric instruments, Anal. Chem., vol. 68, pp. 982-990 (1996) and M. Defemez, R. Wilson, Infrared spectroscopy: instrumental factors affecting the long-term validity of chemometric models, Anal. Chem., vol. 69, pp. 1288-1294 (1997), and E. Bouveresse, D. Massart, P. Dardenne, Calibralion transfer across near-infrared spectrometric instruments using Shenk's algorithm: effects of different standardization samples, Analytica Chimica Acta, vol. 297, pp. 405-416, (1994) and Y. Wang, D. Veltkamp, B. Kowalski, Multivariate instrument calibration, Anal. Chem., vol. 63, pp. 2750-2756 (1991).
Most of the reported methods of calibration transfer have been applied in situations involving high-concentration analytes, wherein the signal-to-noise ratio is high. Because these currently known methods act as a smoothing function when transferring calibrations, they degrade the signal to noise that can be observed, thus hindering analysis of low concentration analytes. Additional problems of changes in resolution or bandwith across time or between instruments have not been addressed.
Furthermore, the currently known methods have only been successfully applied in situations involving a small number of instruments. The reported methods are not capable of modeling the complexity encountered when large numbers of instruments are involved.
A need exists for the calibration of large numbers of analyzers. It would be desirable to provide a means of reducing the complexity inherent in the transfer of calibrations to large numbers of analyzers. It would also be advantageous to provide a means of transferring calibrations without significant degradation of the signal-to-noise ratio, rendering calibration transfer practical in analysis of low concentration analytes.